I am a motivated MSc Artificial Intelligence & Data Science student at the University of East London, with a strong foundation in Python, machine learning pipelines, and LLM application development. I am currently building hands-on AI projects, including a RAG-based Q&A system and a semantic job-matching tool.
I am seeking an AI/ML Engineering internship in London where I can apply my technical skills in a real-world environment and continue deepening my knowledge. My academic work focuses on machine learning, deep learning, natural language processing, and data engineering.
I have practical experience developing projects with Python, LangChain, ChromaDB, Streamlit, OpenAI API, and scikit-learn. These projects have helped me build a solid understanding of embeddings, vector databases, retrieval-augmented generation, and prompt engineering.
I also hold a BSc in Computer Science, Mathematics & Physics, which gave me strong foundations in algorithms, data structures, statistics, and linear algebra. This background supports my understanding of machine learning concepts and model behavior.
In addition to my studies, I have worked as a Warehouse Operative in Leicester, where I developed reliability, attention to detail, and the ability to work under pressure in a fast-paced environment. I have also balanced full-time work with self-funding my MSc, which reflects my drive and time management.
I am based in Leicester, UK, and I am open to opportunities in London. I have full right to work in the UK and am available for summer or year-round internship roles.
In progress. Core modules include Machine Learning, Deep Learning, Natural Language Processing, and Data Engineering. Actively building AI portfolio projects in Python, LangChain, and scikit-learn.
First Class, 6.5 CGPA. Built strong foundations in algorithms, data structures, statistics, and linear algebra.
Maintained consistent high performance in a fast-paced, target-driven logistics environment. Demonstrated reliability, attention to detail, and ability to work under pressure. Self-funded MSc studies while working full-time, demonstrating exceptional drive and time management.
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